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Rebecca, V.

Publications and source records attributed to Rebecca, V..

3 recordsLinked to original sources

Single-cell RNA sequencing reveals dysregulated fibroblast subclusters in prurigo nodularis

Prurigo nodularis (PN) is an intensely pruritic, chronic inflammatory skin disease that disproportionately affects black patients. However, the pathogenesis of PN is poorly understood. We performed single-cell transcriptomic profiling, ligand receptor analysis and cell trajectory analysis of 28,695 lesional and non-lesional PN skin cells to uncover disease-identifying cell compositions and genetic characteristics. We uncovered a dysregulated role for fibroblasts (FBs) and myofibroblasts as a key pathogenic element in PN, which were significantly increased in PN lesional skin. We defined seven unique subclusters of FBs in PN skin and observed a shift of PN lesional FBs towards a cancer-associated fibroblast (CAF)-like phenotype, with WNT5A+ CAFs increased in the skin of PN patients and similarly so in squamous cell carcinoma (SCC). A multi-center PN cohort study subsequently revealed an increased risk of SCC as well as additional CAF-associated malignancies in PN patients, including breast and colorectal cancers. Systemic fibroproliferative diseases were also upregulated in PN patients, including renal sclerosis and idiopathic pulmonary fibrosis. Ligand receptor analyses demonstrated increased FB1-derived WNT5A and periostin interactions with neuronal receptors MCAM and ITGAV, suggesting a fibroblast-neuronal axis in PN. Type I IFN responses in immune cells and increased angiogenesis/permeability in endothelial cells were also observed. As compared to atopic dermatitis (AD) and psoriasis (PSO) patients, increased mesenchymal dysregulation is unique to PN with an intermediate Th2/Th17 phenotype between atopic dermatitis and psoriasis. These findings identify a pathogenic role for CAFs in PN, including a novel targetable WNT5A+ fibroblast subpopulation and CAF-associated malignancies in PN patients.

bioinformatics↗

Conservation of copy number profiles during engraftment and passaging of patient-derived cancer xenografts

Patient-derived xenografts (PDXs) are resected human tumors engrafted into mice for preclinical studies and therapeutic testing. It has been proposed that the mouse host affects tumor evolution during PDX engraftment and propagation, impacting the accuracy of PDX modeling of human cancer. Here we exhaustively analyze copy number alterations (CNAs) in 1451 PDX and matched patient tumor (PT) samples from 509 PDX models. CNA inferences based on DNA sequencing and microarray data displayed substantially higher resolution and dynamic range than gene expression-based inferences, and they also showed strong CNA conservation from PTs through late-passage PDXs. CNA recurrence analysis of 130 colorectal and breast PT/PDX-early/PDX-late trios confirmed high-resolution CNA retention. We observed no significant enrichment of cancer-related genes in PDX-specific CNAs across models. Moreover, CNA differences between patient and PDX tumors were comparable to variations in multi-region samples within patients. Our study demonstrates the lack of systematic copy number evolution driven by the PDX mouse host.

cancer biology↗

Systematic Establishment of Robustness and Standards in Patient-Derived Xenograft Experiments and Analysis

Patient-Derived Xenografts (PDXs) are tumor-in-mouse models for cancer. PDX collections, such as those supported by the NCI PDXNet program, are powerful resources for preclinical therapeutic testing. However, variations in experimental design and analysis procedures have limited interpretability. To determine the robustness of PDX studies, the PDXNet tested temozolomide drug response for three pre-validated PDX models (sensitive, resistant, and intermediate) across four blinded PDX Development and Trial Centers (PDTCs) using independently selected SOPs. Each PDTC was able to correctly identify the sensitive, resistant, and intermediate models, and statistical evaluations were concordant across all groups. We also developed and benchmarked optimized PDX informatics pipelines, and these yielded robust assessments across xenograft biological replicates. These studies show that PDX drug responses and sequence results are reproducible across diverse experimental protocols. Here we share the range of experimental procedures that maintained robustness, as well as standardized cloud-based workflows for PDX exome-seq and RNA-Seq analysis and for evaluating growth.

cancer biology↗